The overall goal of this project is to evaluate statistical genetic methods for detecting, characterizing, and mapping the genes that influence complex diseases and their precursors and risk factors. We will pursue this goal by: (l) Continuing the organization of the Genetic Analysis Workshops (GAWs). The Genetic Analysis Workshops are a collaborative effort among genetic epidemiologists to evaluate and compare statistical genetic methods. For each GAW, topics are chosen for their relevance to current analytical issues in genetic epidemiology, and sets of computer-simulated or real data are distributed to investigators worldwide. Results of analyses are discussed and compared at a 2 1/2 day meeting. GAW10 will be held in 1996, and GAW11, in 1998. Planning and data distribution for GAW12 will be ongoing by the end of the requested period of support in 2000. (2) Conducting evaluations of methods of genetic analysis. Some issues concerning the strengths and limitations of statistical genetic methods can be more readily addressed outside a workshop setting. Using computer- simulated data, we will address questions of power or sensitivity, specificity, and robustness of various analytical methods. Because many current analytical problems in genetic epidemiology involve complex diseases with associated quantitative precursors and risk factors, we will focus on analysis of such quantitative traits. We will evaluate (l) the utility of multivariate linkage analysis for detecting loci that contribute to quantitative traits, and (2) the effects on statistical inference of including or disregarding genotype x environment (GxE) interaction. This research will complement the Workshops in the sense that many of the same simulation programs and data sets will be used, and special problems that are revealed in the Workshops will be pursued in greater detail. (3) Distributing simulation programs, simulated data, and programs for genetic analysis. As a result of our efforts in generating data for the GAWs and in evaluating methods of genetic analysis, we are developing computer programs and simulated data sets that are of potential value to other investigators. We will continue to document these programs and data sets and provide them to interested investigators.